Development of an Artificial Intelligence-Supported Hybrid Data Management Platform for Monitoring Depression and Anxiety Symptoms in the Perinatal Period: Pilot-Scale Study-Reference-Cited by-同舟云学术

Development of an Artificial Intelligence-Supported Hybrid Data Management Platform for Monitoring Depression and Anxiety Symptoms in the Perinatal Period: Pilot-Scale Study

Published:2023 Issue: Volume:11 Page:31456-31466
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Oğur Nur Banu¹^ORCID,Çeken Celal¹^ORCID,Oğur Yavuz Selİm²,Yuvaci Hİlal Uslu³,Yazici Ahmet Bülent²^ORCID,Yazici Esra²^ORCID

Affiliation:

1. Department of Computer Engineering, Faculty of Computer and Information Sciences, Sakarya University, Sakarya, Turkey

2. Department of Psychiatry, Faculty of Medicine, Sakarya University, Sakarya, Turkey

3. Department of Obstetrics and Gynecology, Faculty of Medicine, Sakarya University, Sakarya, Turkey

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10082938.pdf?arnumber=10082938

Reference40 articles.

1. Demographic and offence characteristics: a comparison of sex offenders convicted of possessing indecent images of children, committing contact sex offences or both offences

2. Using methods from the data-mining and machine-learning literature for disease classification and prediction: a case study examining classification of heart failure subtypes

3. Perinatal Generalized Anxiety Disorder: Assessment and Treatment

4. Testing a machine-learning algorithm to predict the persistence and severity of major depressive disorder from baseline self-reports

5. Overtreatment: Is a solution possible?

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